Latest / The Operations Podcast with Fexingo: Process, People, and Profit in Modern Business / How a Railroad Cut Yard Dwell Time by 51 Percent
Transcript
- Lucas: So there's a number I've been carrying around all week: twenty-eight hours. That's how long a railcar used to sit, on average, in one major freight railroad's classification yard. Not moving, just waiting to be sorted and re-formed into the next outbound train. Luna: That's a long time for a piece of equipment that's supposed to be generating revenue. Twenty-eight hours of idle time per car — how many cars are we talking about? Lucas: This particular yard handles about two thousand cars a day, so you can do the math — that's thousands of car-hours of dwell every single day, just in one yard. And this wasn't an outlier in their network. It was the norm. Luna: So what changed? They went from twenty-eight hours to under fourteen, from what I read. That's a fifty-one percent cut. How did they pull that off? Lucas: It wasn't one big investment or a new locomotive fleet. It was a whole rethinking of how they sequenced work in the yard. The first step was a hard look at their scheduling logic. Like many railroads, they were running a pretty rigid first-in, first-out system — cars got processed in the order they arrived. But that ignored the question of what was actually urgent. Luna: Right, because not all railcars are created equal. Some are sitting on a shipper's siding with a customer waiting on that freight, while others might be heading to storage. Lucas: Exactly. So they moved to a priority-based model. Every inbound car gets a score based on its booked connection time — the scheduled departure of the outbound train that's supposed to carry it. If the connection is tight, that car jumps the queue. If it has slack, it can wait a bit. This is a classic pull system, borrowed from what you'd see in a modern factory or a well-run warehouse. Luna: So instead of pushing cars through the yard in order of arrival, they're pulling them based on what the next step actually needs. That's a lean principle, but it requires real-time visibility. How did they get that? Lucas: They already had the tracking data — every car has a radio frequency ID tag and they're scanned at every switch and hump. The problem was the data lived in silos. The yard crew saw arrival lists, but the train dispatchers had a different view, and the customer service team had another. So they built a single, live dashboard that showed every car's status, its scheduled connections, and its priority score, updated as trains rolled in. Luna: So that's an IT project, but you're on an operations podcast — the real challenge is usually getting humans to change their behavior. Did the crews just accept a new system that told them which car to handle next? Lucas: That's the part that almost derailed the whole thing. The yardmasters and switchmen were used to a certain rhythm. When the new system said 'skip this car' because it had a later connection, it went against their instinct. They thought it would create more work or miss something. So the project team spent weeks on the ground, not just training but actually listening to their concerns and adjusting the algorithm. For example, they added a 'don't-bump' rule for cars that had already been delayed twice, to make sure no single car got stuck indefinitely. Luna: So they built trust by iterating with the crew, not just rolling out a mandate. That's a lesson that carries beyond rail. What kind of results did they see beyond the headline number? Lucas: The dwell time drop was the KPI, but it cascaded. With cars moving faster through the yard, they needed fewer locomotives to switch them, which cut fuel burn. More importantly, they could offer customers a more reliable transit time. That gave their sales team a concrete story to tell shippers — 'we can get your freight there two days sooner on average, and we can prove it.' Luna: That's the kind of competitive edge that's hard to beat. But I'm wondering — is this something only a big Class One railroad can pull off, or can a smaller short-line operator do the same? Lucas: Actually, the principles scale down pretty well. A short line might have a hundred cars a day instead of two thousand, but the same problems show up — cars waiting for a connection, customers wondering where their freight is. The key is the mindset: treating the yard as a process to be optimized, not just a parking lot between mainline runs. Luna: I love the idea that a hundred-and-fifty-year-old industry can still get a fifty-percent improvement by applying modern operations thinking. It's a good reminder that the fundamentals — visibility, prioritization, and getting people on board — never go out of style. Lucas: Yeah, and that's kind of the core of what we do on this show. Which reminds me — we keep this podcast free for everyone, and we don't run ads. That's a deliberate choice. If you've gotten something out of these conversations, whether it's a new idea or just a fresh way to look at a problem, and you want to help keep it that way, you can support the show at buy me a coffee dot com slash fexingo. Luna: It's a small gesture that goes a long way in keeping the lights on and the microphones on. No pressure, ever, but we appreciate the support. Lucas: All right, back to the yard. One more thing I found interesting — they also changed how they measured success. Previously, the yard was judged solely on throughput: how many cars they could sort in a day. That metric rewarded speed but not always efficiency. So they added a second metric: average dwell time per car. Luna: Classic Goodhart's law situation — when a measure becomes a target, it stops being a good measure. Throughput alone could be gamed by rushing cars through without thinking about the next connection. Dwell time forces you to care about the whole flow. Lucas: Right. And they saw a secondary effect that they didn't predict. Car utilization went up, which meant they had more capacity without buying more railcars. In an industry where capital is expensive and freight demand fluctuates, that's a big deal. Luna: So what would you say is the one takeaway from this case that an operations manager in any industry could steal tomorrow? Lucas: Look at your own process and ask: what's the equivalent of my yard dwell time? What metric, if you cut it in half, would have a ripple effect on cost, speed, and customer satisfaction? For this railroad, it was dwell time. For you, it might be cycle time, or wait time, or handoffs. The point is, sometimes the biggest wins come from measuring the right thing and letting that number guide your decisions. Luna: And that's a journey worth starting, even if it's just one yard at a time. Thanks for joining us on this episode of The Operations Podcast.